Whole exome sequencing in Finnish families identifies new candidate genes for osteoarthritis

A Review of the Role of Bioreactors for iPSCs-Based Tissue-Engineered Articular Cartilage

BACKGROUND

Osteoarthritis (OA) is the most common degenerative joint disease without an ultimate treatment. In a search for novel approaches, tissue engineering (TE) has shown great potential to be an effective way for hyaline cartilage regeneration and repair in advanced stages of OA. Recently, induced pluripotent stem cells (iPSCs) have been appointed to be essential stem cells for degenerative disease treatment because they allow a personalized medicine approach. For clinical translation, bioreactors in combination with iPSCs-engineerd cartilage could match patients needs, serve as platform for large-scale patient specific cartilage production, and be a tool for patient OA modelling and drug screening. Furthermore, to minimize in vivo experiments and improve cell differentiation and cartilage extracellular matrix (ECM) deposition, TE combines existing approaches with bioreactors.

METHODS

This review summarizes the current understanding of bioreactors and the necessary parameters when they are intended for cartilage TE, focusing on the potential use of iPSCs.

RESULTS

Bioreactors intended for cartilage TE must resemble the joint cavity niche. However, recreating human synovial joints is not trivial because the interactions between various stimuli are not entirely understood.

CONCLUSION

The use of mechanical and electrical stimulation to differentiate iPSCs, and maintain and test chondrocytes are key stimuli influencing hyaline cartilage homeostasis. Incorporating these stimuli to bioreactors can positively impact cartilage TE approaches and their possibility for posterior translation into the clinics.

Understanding Musculoskeletal Disorders Through Next-Generation Sequencing

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An insight into musculoskeletal disorders through advancements in next-generation sequencing (NGS) promises to maximize benefits and improve outcomes through improved genetic diagnosis.

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The primary use of whole exome sequencing (WES) for musculoskeletal disorders is to identify functionally relevant variants.

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The current evidence has shown the superiority of NGS over conventional genotyping for identifying novel and rare genetic variants in patients with musculoskeletal disorders, due to its high throughput and low cost.

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Genes identified in patients with scoliosis, osteoporosis, osteoarthritis, and osteogenesis imperfecta using NGS technologies are listed for further reference.

Understanding osteoarthritis pathogenesis: a multiomics system-based approach

PURPOSE OF REVIEW

Osteoarthritis is a heterogeneous, multifactorial condition regulated by complex biological interactions at multiple levels. Comprehensive understanding of these regulatory interactions is required to develop feasible advances to improve patient outcomes. Improvements in technology have made extensive genomic, transcriptomic, epigenomic, proteomic, and metabolomic profiling possible. This review summarizes findings over the past 20 months related to omics technologies in osteoarthritis and examines how using a multiomics approach is necessary for advancing our understanding of osteoarthritis as a disease to improve precision osteoarthritis treatments.

RECENT FINDINGS

Using the search terms 'genomics' or 'transcriptomics' or 'epigenomics' or 'proteomics' or 'metabolomics' and 'osteoarthritis' from January 1, 2018 to August 31, 2019, we identified advances in omics approaches applied to osteoarthritis. Trends include untargeted whole genome, transcriptome, proteome, and metabolome analyses leading to identification of novel molecular signatures, cell subpopulations and multiomics validation approaches.

SUMMARY

To address the complexity of osteoarthritis, integration of multitissue analyses by multiomics approaches with the inclusion of longitudinal clinical data is necessary for a comprehensive understanding of the disease process, and for appropriate development of efficacious diagnostics, prognostics, and biotherapeutics.

Common variants in IL17F gene contributed to the risk of hip osteoarthritis susceptibility in Han Chinese population

AIM

The prevalence of hip and knee osteoarthritis (OA) varies by ethnicity, suggesting genetic heterogeneity in populations and predilection sites. Given the unknown mechanism of IL17F gene in the etiology of OA, it is necessary to examine the potential shared susceptibility of IL17F gene between knee OA and hip OA (HOA). This study aimed to evaluate the association of the IL17F gene and susceptibility to HOA in a Han Chinese population.

METHODS

A total of 2650 study subjects, comprising 796 HOA patients and 1854 controls, were recruited into the present study. Seven tag single nucleotide polymorphisms (SNPs) were selected for genotyping. Single marker-based genetic association analyses were conducted at both the genotypic and allelic levels. χ² statistics were calculated for statistical testing, and odds ratios were obtained to estimate the effects of genotypes and alleles for each SNP.

RESULTS

The SNP rs763780 was identified to be significantly associated with the risk of HOA at both genotypic (χ²  = 12.45, P = .002) and allelic levels (χ²  = 11.83, P = .0006). A linkage disequilibrium (LD) block comprised of 3 SNPs (rs12201582-rs12203736-rs722323) was also significantly associated with the risk of HOA. In addition, rs2294835 was identified to be associated with HOA severity (χ²  = 12.10, P = .02).

CONCLUSION

Our results showed that IL17F gene contributed to the risk of HOA in a Han Chinese population, which would help to elucidate the pathogenesis of OA and facilitate the development of novel medicines and treatments for OA.

Cell cycle-related lncRNAs and mRNAs in osteoarthritis chondrocytes in a Northwest Chinese Han Population

BACKGROUND

A group of differentially expressed long non-coding RNAs (lncRNAs) have been shown to play key roles in osteoarthritis (OA), although they represented only a small proportion of lncRNAs that may be biologically and physiologically relevant. Since our knowledge of regulatory functions of non-coding RNAs is still limited, it is important to gain better understanding of their relation to the pathogenesis of OA.

METHODS

We performed mRNA and lncRNA microarray analysis to detect differentially expressed RNAs in chondrocytes from three OA patients compared with four healthy controls. Then, enrichment analysis of the differentially expressed mRNAs was carried out to define disease molecular networks, pathways and gene ontology (GO) function. Furthermore, target gene prediction based on the co-expression network was performed to reveal the potential relationships between lncRNAs and mRNAs, contributing an exploration of a role of lncRNAs in OA mechanism. Quantitative RT-PCR analyses were used to demonstrate the reliability of the experimental results.

FINDINGS

Altogether 990 lncRNAs (666 up-regulated and 324 down-regulated) and 546 mRNAs (419 up-regulated and 127 down-regulated) were differentially expressed in OA samples compared with the normal ones. The enrichment analysis revealed a set of genes involved in cell cycle. In total, 854 pairs of mRNA and lncRNA were highly linked, and further target prediction appointed 12 genes specifically for their corresponding lncRNAs. The lncRNAs lncRNA-CTD-2184D3.4, ENST00000564198.1, and ENST00000520562.1 were predicted to regulate SPC24, GALM, and ZNF345 mRNA expressions in OA.

INTERPRETATION

This study uncovered several novel genes potentially important in pathogenesis of OA, and forecast the potential function of lnc-CTD-2184D3.4, especially for the cell cycle in the chondrocytes. These findings may promote additional aspects in studies of OA.

Evaluation of Common Variants in the AKNA Gene and Susceptibility to Knee Osteoarthritis Among the Han Chinese

Background: Osteoarthritis (OA) is a complex degenerative joint disease that is associated with both genetic and environmental factors. The AKNA gene, located at 9q32, has recently been identified as being associated with knee osteoarthritis (KOA) in the Mexican population. Our aim was to investigate the relationship of common variants in this gene with the risk of KOA in a large Han Chinese population. Methods: A total of 2,500 Han Chinese subjects were recruited, consisting of 824 KOA patients and 1,676 controls. Eight tag single nucleotide polymorphisms (SNPs) located within the ANKA gene were selected for genotyping. Single marker-based association analyses were conducted using multiple modes of inheritance, including genotypic, allelic, dominant, and recessive. Haplotype-based association analyses were also performed. Plink was utilized for genetic association analyses. In addition, we examined the GTEx database to test the expression quantitative loci effects of the significant SNPs within the AKNA gene. Results: Among these eight SNPs evaluated we identified one, rs10817595, as being significantly associated with the risk of KOA. Compared to the CC genotype at this locus, the odds ratio (95% confidence interval) for KOA with the AA genotype was 1.58 (1.23-2.01)-fold greater. A linkage disequilibrium block that included this SNP was also determined to be significantly associated with the risk of KOA (χ² = 25.08, p = 3.58 × 10^-6). In general, the minor allele A of SNP rs10817595 was associated with an increased risk of KOA. Conclusion: This study is the first to present evidence for a potential link between the risk of KOA and an AKNA gene polymorphism among persons with a Han Chinese ancestry. Future functional analyses based on animal models and sequencing-based population studies are needed to elucidate the biological plausibility and genetic architecture of AKNA for KOA susceptibility.